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Fight Property Insurance Fraud with Advanced Analytics

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One of the biggest pain points keeping insurance carriers up at night is fraud. With an uptick in mortgages increasing the demand for new homeowners policies, insurance carriers must improve new business underwriting performance to limit losses while meeting revenue growth objectives. But to do this, they have to address some critical questions. For instance, what does it mean to target fraud with analytics? How do I know where to focus to mitigate fraud? How do I gain high returns and book more business?

To make better-informed decisions, insurers are turning to alternative data, analytics, and models to improve the application process, determine unacceptable risk and price policies more accurately, all while identifying fraudulent activity.

Improving underwriting performance is no longer a mirage in the distance. There is a significant opportunity to take action on a small percentage of your book and gain high returns.

To ensure a profitable fraud strategy and improved underwriting performance, carriers should target properties with the highest potential for loss. With the right data and analytics, carriers can predict large losses-those that are greater than or equal to 80% of coverage. TransUnion’s performance analytics database has shown there is 140% higher occurrence of large losses in the 1% of properties with the highest risk score.1

Further analytics from the TransUnion Property Risk Verification PlatformSM solution have shown we can classify 5% of new business policies as “high-risk” from an occupancy, identity, mortgage, property or insurable interest perspective. These risk have 1.5 to 2 times the loss ratio relativity compared to the less risky 95%. Using a solution like this allows carriers to identify higher claims frequencies and identify high- and medium- risk groups.

The key is to use insights that are predictive, timely, easy to understand and implementable through existing carrier processes. Leveraging analytics in fraud strategy helps to more accurately identify policies with the highest potential for claims.

By using property verification solutions, carriers can take action on a small number of high-risk applications that have a high probability of loss. These solutions help carriers quickly identify ineligible risk and avoid binding business that could be costly.

Read the insight guide Predictive Power for more ways analytics can help you identify high-risk properties.


  1. TransUnion Performance Analytics Database 2009-2014 Risk Verification Platform data studies. Standard and Non-Standard Policies. Not all states included.
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